DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
The drawings are objected to because of the following informalities.
The view numbers must be larger than the numbers used for reference characters. See 37 C.F.R. 1.84(u)(2).
Corrected drawings in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. The replacement sheet(s) should be labeled “Replacement Sheet” in the page header (as per 37 CFR 1.84(c)) so as not to obstruct any portion of the drawing figures. If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Title
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Examiner believes that the title of the invention is imprecise. A descriptive title indicative of the invention will help in proper indexing, classifying, searching, etc. See MPEP 606.01. However, the title of the invention should be limited to 500 characters. Examiner suggests including the aspect(s) of the claims which Applicant believes to be novel or nonobvious over the prior art.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: DeepES units introduced in claim 1; the initialization module is used for initializing; the first state calculation module is used for calculating; the iterative calculation module is used for outputting; and the prediction module is used for calculating in claim 13.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
The structure for the DeepES unit was found in paragraph 88 which states, “The DeepES unit and the network modules are components of the neural network. The structures for carrying these components can each be one or more processors or chips with communication interfaces that are capable of implementing communication protocols. If necessary, these structures can also include memories and relevant interfaces, system transport buses, etc. The processors or chips execute program-related codes to achieve respective functions.” Therefore, the DeepES units are interpreted as software run on generic hardware.
The structure for these modules was found in paragraph 98 of the specification. Specifically, “the initialization module, the first state calculation module, the iterative calculation module, and the prediction module can each be one or more processors or chips with communication interfaces that are capable of implementing communication protocols. If necessary, they can also include memories and relevant interfaces, system transport buses, etc. The processors or chips execute program-related codes to achieve respective functions. Or, an alternative approach may be that the initialization module, the first state calculation module, the iterative calculation module, and the prediction module share an integrated chip, or share a processor, a memory, and other devices. The shared processor or chip executes relevant codes to implement the respective functions.” Accordingly, these modules are interpreted as software run on generic hardware.
Claim Objections
The following claims are objected to because of the following informalities:
Claim for clarity should recite a seasonal factor, a trend factor, and a smoothing factor.
Claim 3 recites obtaining a value Xinit through InitNet network for initializing the factors. The term InitNet network was not previously introduced, so should be recited as an InitNet network. Subsequent recitations should use the InitNet network.
Claim 3 recites for initializing the factors, but should recite for initializing the three factors.
Claim 3 does not end in a period. Each claim is a sentence and therefore must end in a period. See MPEP 608.01(m). Examiner understands the claim ends in an equation so may require rephrasing.
Claim 3 recites through InitNet network, but since this is the first introduction of that element, it should recite through a InitNet network.
Claim 5 should recite wherein the step 2 of calculating states.
Claim 13 in the fourth indentation contains two limitations. The limitation calculating iteratively the states of the three factors for the time t+1 in the DeepES unit until a n-th DeepES unit completes its operation should be indented on the next line.
Appropriate correction is required.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The claims contain numerous indefiniteness issues. While Examiner attempted to find all instances, the extent of the issues may have resulted in some being missed. Applicant should thoroughly review the claims to ensure clarity and consistency.
For Claim 1:
time t+1 – This is not necessarily the state after S1, T1, or I1, and when it is not the limitation is unclear. For example, when S1 is followed by time 5 (so time 5+1), it is unclear how the system jumped from 1 to 6.
namely S1+t, T1+t, and It+1 – This phrasing using namely appears to suggest these are examples which would render the claim indefinite since it is unclear if the scope of the claim includes them or not.
the three factors St+1, Tt+1, and It+1 – The claim previously recited initializing three factors - seasonal factor, trend factor, and smoothing factor, denoted as Si, Ti, and I1 respectively. The phrase the three factors are referring to two separate sets of three elements. It is also repeated in step 5.
step 4, repeating steps 2 to 3 until a n-th DeepES unit completes its operation – This recitation indicates that step 2 and 3 are repeated; however, the time in the claim is never advanced. Therefore, step 2 calculates the same state values for the three factors at the same time repeatedly and advances those same values. How the method arrives at a solution using this single value for each variable is unclear.
a n-th Deep ES unit - The variable n-th is not defined in the claim.
a predicted value Y – The variable Y is not defined. It is unclear exactly what is being predicted.
For Claim 2:
steps 1 to 3 comprise – Steps 1 to 3 was previously introduced. It is unclear if this is the same element, a different element, or related elements.
For Claim 3:
the process – This element has no proper antecedent basis.
a length of the input sequence is n – It is unclear of the variable n in this claim is the same element, a different element, or a related element to a n-th DeepES unit in claim 1.
after obtaining the three metrics – There is no antecedent basis since the three metrics were not obtained. It is likely referencing calculating a mean, a variance, and a horizontal proportion. Therefore, the three metrics were calculated, not obtained.
The term p in the equations on lines 14-16 is not defined.
For Claim 4:
wherein InitNet network's parameters – While the InitNet network was previously introduced, the fact that it has parameters was not disclosed.
a number of input samples - This phrase is used numerous times in the claim. It is unclear if this is the same element, a different element, or related elements.
a dimension of sample characteristics – This phrase is used numerous times in the claim. It is unclear if this is the same element, a different element, or related elements.
a number of samples - This phrase is used numerous times in the claim. It is unclear if this is the same element, a different element, or related elements. As a side note, this phrase refers to the output dimension, so should recite a number of output samples for clarity’s sake.
In this claim, several different variables are referred to using one of the above phrases. For example, both k and p are recited as a dimension of sample characteristics. It is unclear if this is the same element, a different element, or related elements.
For Claim 5:
the currently executing step is t – It is unclear if this is referring to one of steps 1 to 5 from claim 1, or if this was intended to be a time step.
the smoothing factor It+1 – This lacks clear antecedent basis. Previously, the smoothing factor was denoted as I1 in claim 1.
The left sides of the two equations on lines 8 and 9 are not defined.
TempNet refers to TempNet calculation network – The term refers is indefinite because it does not indicate the metes and bounds of the relationship.
TempNet refers to TempNet calculation network – The term TempNet calculation network is first being introduced here and should recite a TempNet calculation network.
TempNet's parameters – While the TempNet calculation network was previously introduced, the fact that it has parameters was not disclosed.
Claim 6:
the trend factor Tt+1 – As defined in claim 1, the trend factor is T1. It is unclear if this is the same element, a different element, or related elements.
p1 – This term is not defined.
TempNet refers to TempNet calculation network – The term refers is indefinite because it does not indicate the metes and bounds of the relationship.
TempNet refers to TempNet calculation network – The term TempNet calculation network was previously introduced in claim 5. It is unclear if this is the same element, a different element, or related elements.
Claim 7:
the seasonal factor Tt+1 – As defined in claim 1, the seasonal factor is S1. It is unclear if this is the same element, a different element, or related elements.
p1 – This term is not defined.
a concatenation operation of two vectors – Was previously introduced. It is unclear if this is the same element, a different element, or related elements.
TempNet refers to TempNet calculation network – The term refers is indefinite because it does not indicate the metes and bounds of the relationship.
TempNet refers to TempNet calculation network – The term TempNet was previously introduced in claim 5. It is unclear if this is the same element, a different element, or related elements.
TempNet refers to TempNet calculation network – The term TempNet calculation network was previously introduced in claim 5. It is unclear if this is the same element, a different element, or related elements.
Claim 8:
Same issues as claim 5.
Claim 9:
Same issues as claim 6.
Claim 10:
Same issues as claim 7.
Claim 11:
namely Slast, Tlast, and Ilast – This phrasing using namely appears to suggest these are examples which would render the claim indefinite.
PreNet refers to PreNet calculation network – The term refers is indefinite because it does not indicate the metes and bounds of the relationship.
PreNet calculation network – This term is being introduced here and should recite a PreNet calculation network.
PreNet prediction network's parameters – While the PreNet prediction network was previously introduced, the fact that it has parameters was not disclosed.
a number of input samples – This term is repeated multiple times. It is unclear if this is the same element, a different element, or related elements.
a dimension of sample characteristics - This term is repeated multiple times. It is unclear if this is the same element, a different element, or related elements.
an output dimension - This term is repeated multiple times. It is unclear if this is the same element, a different element, or related elements.
a number of samples - This term is repeated multiple times. It is unclear if this is the same element, a different element, or related elements.
a dimension of sample characteristics is 1 – The last line of this claim states that a dimension of sample characteristics is 1, while a previous line recites that a dimension of sample characteristics is p. This reasonably means that p = 1. Therefore, the dimensions of the first hidden layer are [1, 3], the dimensions of the second hidden layer are [1, 1], and the dimensions of the output layer are [1, 1].
Claim 12:
Same issues as claim 11.
Claim 13:
Same issues as claim 1.
Claim 14:
Same issues as claim 1.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claim 1 is a method claim. Claim 13 is a system claim. Claim 14 is a machine claim. Therefore, claims 1, 13, and 14 are directed to either a process, machine, manufacture or composition of matter.
With respect to Claim 1:
Step 2A Prong 1:
step 1, initializing three factors - seasonal factor, trend factor, and smoothing factor, denoted as S1, T1, and I1 respectively (mental process – user can manually initialize the three factors)
step 2, calculating states of the three factors for time t+1 in a current DeepES unit, namely S1+t, T1+t, and It+1 (mental process – user can manually calculate states of the three factors for time t+1)
step 4, repeating steps 2 to 3 until a n-th DeepES unit completes its operation (mental process – user can manually repeat the steps until complete)
step 5, calculating a predicted value Y based on the three factors that are outputted from a final DeepES unit (mental process – user can manually calculate a predicted value based on the factors)
Step 2A Prong 2: This judicial exception is not integrated into a practical application. Additional elements:
step 2, calculating states of the three factors for time t+1 in a current DeepES unit, namely S1+t,T1+t, and It+1 (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
step 3, outputting the three factors St+1, Tt+1, and It+1 to a next DeepES unit (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
step 4, repeating steps 2 to 3 until a n-th DeepES unit completes its operation (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
step 5, calculating a predicted value Y based on the three factors that are outputted from a final DeepES unit (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Step 2B: The claim does not include additional elements considered individually and in combination that are sufficient to amount to significantly more than the judicial exception. Additional elements:
step 2, calculating states of the three factors for time t+1 in a current DeepES unit, namely S1+t,T1+t, and It+1 (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
step 3, outputting the three factors St+1, Tt+1, and It+1 to a next DeepES unit (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
step 4, repeating steps 2 to 3 until a n-th DeepES unit completes its operation (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
step 5, calculating a predicted value Y based on the three factors that are outputted from a final DeepES unit (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f))
Conclusion: The claim is not patent eligible.
Claims 13 and 14 are rejected on the same grounds as claim 1. Additionally for claims 13 and 14: Claim 13 has the additional elements of an initialization module, a first state calculation module, an iterative calculation module, and a prediction module. These elements are mere instructions to apply the exception using a generic computer component under Step 2A prong 2 and Step 2B. Claim 14 has the additional element of a memory and a processor. This element is mere instructions to apply the exception using a generic computer component under Step 2A prong 2 and Step 2B.
Regarding Claim 2: The limitation(s), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind. That is, other than the additional elements, nothing in the claim limitation(s) precludes the step from practically being performed in the mind.
The limitation(s) encompasses the user manually constructing a network framework;
setting an activation function within the network framework and utilizing the network framework to calculate the states of the three factors for the time t+l in the current DeepES unit.
The limitation(s) includes the additional elements of setting an activation function within the network framework and utilizing the network framework to calculate the states of the three factors for the time t+l in the current DeepES unit;
outputting, by the current DeepES unit, the St1+,Tt+i, and I t.1 calculated by the network framework to the next DeepES unit.
These judicial exceptions are not integrated into a practical application. The additional element(s) of in the current DeepES unit; outputting, by the current DeepES unit, the St1+,Tt+i, and I t.1 calculated by the network framework to the next DeepES unit recite merely adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Accordingly, this does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element(s) of in the current DeepES unit; outputting, by the current DeepES unit, the St1+,Tt+i, and I t.1 calculated by the network framework to the next DeepES unit recite adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Accordingly, the claims are not patent eligible.
Regarding Claim 3: The limitation(s), as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind and/or mathematical concepts. That is, nothing in the claim limitation(s) precludes the step from practically being performed in the mind and/or include merely mathematical concepts.
The limitation(s) encompasses the user manually given an input sequence {X1,X2,...,Xn}, where X represents power load data and a length of the input sequence is n;
taking first k values of the input sequence, denoted as {X1,X2,...,Xk}, calculating a mean, a variance, and a horizontal proportion of the input sequence, wherein the calculation formulas for these three metrics are as follows:
<Xmean equation>
<Xvar equation>
<Xp equation>
after obtaining the three metrics Xmean, Xvar and Xp, obtaining a value Xinit through InitNet network for initializing the factors;
after obtaining Xinit, initializing the three factors as follows:
<S0 equation>
<T0 equation>
<I0 equation>
These judicial exceptions are not integrated into a practical application. In particular, the claims do not recite any additional elements. Accordingly, this does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, no additional elements are cited. Accordingly, the claim is not patent eligible.
Regarding Claim 4: The limitation(s), as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind. That is, nothing in the claim limitation(s) precludes the step from practically being performed in the mind.
The limitation(s) encompasses the user manually an input data dimension of a first hidden layer is [1, k] meaning a number of input samples is 1 and a dimension of sample characteristics is k; an output dimension is [1, p] meaning a number of samples is 1 and a dimension of sample characteristics is p;
an input dimension of a second hidden layer is [1, p] meaning a number of input samples is 1 and a dimension of sample characteristics is p, an output dimension is [1, p] meaning a number of samples is 1 and a dimension of sample characteristics is p;
an input dimension of an output layer is [1, p] meaning a number of input samples is 1 and a dimension of sample characteristics is p; an output dimension is [1, p+2] meaning a number of samples is 1 and a dimension of sample characteristics is p+2.
These judicial exceptions are not integrated into a practical application. In particular, the claims do not recite any additional elements. Accordingly, this does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, no additional elements are cited. Accordingly, the claim is not patent eligible.
Regarding Claim 5: The limitation(s), as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind and/or mathematical concepts. That is, nothing in the claim limitation(s) precludes the step from practically being performed in the mind and/or include merely mathematical concepts.
The limitation(s) encompasses the user manually given that an input sequence is [Xi,X2,...,X}, the number of iterations is n, the currently executing step is t,
calculating the smoothing factor It+1 for the time t+l with the following calculation formulas:
<equation in line 8>
<equation in line 9>
<equation in line 10>
where concat(•) represents a concatenation operation of two vectors and TempNet refers to TempNet calculation network;
TempNet's parameters are configured as follows:
an input dimension of a hidden layer is [1, 2p] meaning a number of input samples is 1 and a dimension of sample characteristics is 2p; an output dimension is [1, p] meaning a number of samples is 1 and a dimension of sample characteristics is p;
an input dimension of an output layer is [1, p] meaning a number of input samples is 1 and a dimension of sample characteristics is p; an output dimension is [1, p] meaning a number of samples is 1 and a dimension of sample characteristics is p.
These judicial exceptions are not integrated into a practical application. In particular, the claims do not recite any additional elements. Accordingly, this does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, no additional elements are cited. Accordingly, the claim is not patent eligible.
Regarding Claim 6: The limitation(s), as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind and/or mathematical concepts. That is, nothing in the claim limitation(s) precludes the step from practically being performed in the mind and/or include merely mathematical concepts.
The limitation(s) encompasses the user manually calculating the trend factor Tt+1 for the time t+1 with the following calculation formulas:
<equation in line 4>
<equation in line 5>
where concat(•) represents a concatenation operation of two vectors and TempNet refers to TempNet calculation network.
These judicial exceptions are not integrated into a practical application. In particular, the claims do not recite any additional elements. Accordingly, this does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, no additional elements are cited. Accordingly, the claim is not patent eligible.
Regarding Claim 7: The limitation(s), as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind and/or mathematical concepts. That is, nothing in the claim limitation(s) precludes the step from practically being performed in the mind and/or include merely mathematical concepts.
The limitation(s) encompasses the user manually calculating the seasonal factor St+1 for the time t+I with the following formulas:
<equation in line 4>
<equation in line 5>
where concat(•) represents a concatenation operation of two vectors and TempNet refers to TempNet calculation network.
These judicial exceptions are not integrated into a practical application. In particular, the claims do not recite any additional elements. Accordingly, this does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, no additional elements are cited. Accordingly, the claim is not patent eligible.
Claim 8 is rejected on the same grounds as claim 5.
Claim 9 is rejected on the same grounds as claim 6.
Claim 10 is rejected on the same grounds as claim 7.
Regarding Claim 11: The limitation(s), as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitation(s) in the mind and/or mathematical concepts. That is, nothing in the claim limitation(s) precludes the step from practically being performed in the mind and/or include merely mathematical concepts.
The limitation(s) encompasses the user manually wherein in step 5, the calculation of the predicted value Y based on the three factors, namely Slast, Tast, and Itast that are outputted from the final DeepES unit is performed with the following calculation formula:
Y = PreNet(concat(Slast, Tlast, Ilast))
where concat(•) represents a concatenation operation of two vectors and PreNet refers to PreNet prediction network;
PreNet prediction network's parameters are configured as follows:
an input data dimension of a first hidden layer is [1, 3p] meaning a number of input samples is 1 and a dimension of sample characteristics is 3p; an output dimension is [1, p] meaning a number of samples is 1 and a dimension of sample characteristics is p;
an input dimension of a second hidden layer is [1, p] meaning a number of input samples is 1 and a dimension of sample characteristics is p; an output dimension is [1, p] meaning a number of samples is 1 and a dimension of sample characteristics is p;
an input dimension of an output layer is [1, p] meaning a number of input samples is 1 and a dimension of sample characteristics is p; an output dimension is [1,1] meaning a number of samples is 1 and a dimension of sample characteristics is 1.
These judicial exceptions are not integrated into a practical application. In particular, the claims do not recite any additional elements. Accordingly, this does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, no additional elements are cited. Accordingly, the claim is not patent eligible.
Claim 12 is rejected on the same grounds as claim 11.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jiang et al. (hereinafter Jiang), Holt-Winters smoothing enhanced by fruit fly optimization algorithm to forecast monthly electricity consumption in view of Han et al. (hereinafter Han), Artificial Neural Network: Understanding the Basic Concepts without Mathematics.
Regarding Claim 1, Jiang discloses an interpretable power load prediction method, wherein the method comprises:
step 1, initializing three factors - seasonal factor, trend factor, and smoothing factor, denoted as S1, T1, and I1 respectively [“trend, stationarity, and seasonal components of time series” §2.1 ¶2; “α, β, and γ are smoothing parameters of the HW model” §2.1 ¶2; “Parameters initialization” Fig. 2];
step 2, calculating states of the three factors for time t+1 [“t is the period of training data” §2.1 ¶2] in a current DeepES unit, namely S1+t, T1+t, and It+1 [Equations 2-4 §2.1 ¶2];
step 3, outputting the three factors St+t, Tt+t, and It+1 [“t is the period of training data” §2.1 ¶] to a next DeepES unit;
step 4, repeating steps 2 to 3 until a n-th DeepES unit completes its operation;
step 5, calculating a predicted value Y based on the three factors [“Forecasting results” Fig. 2] that are outputted from a final DeepES unit.
However, Jiang fails to explicitly disclose step 2, calculating states of the three factors for time t+1 in a current DeepES unit, namely S1+t, T1+t, and It.1;
step 3, outputting the three factors St+t, Tt+t, and It+1 to a next DeepES unit;
step 4, repeating steps 2 to 3 until a n-th DeepES unit completes its operation;
step 5, calculating a predicted value Y based on the three factors that are outputted from a final DeepES unit.
Han discloses step 2, calculating states of the three factors for time t+1 in a current DeepES unit [“Neurons receive signals and generate other signals. That is, they receive input data, perform some processing, and give an output.” pg. 84 §4], namely S1+t, T1+t, and It.1;
step 3, outputting the three factors St+t, Tt+t, and It+1 to a next DeepES unit [“Neurons receive signals and generate other signals. That is, they receive input data, perform some processing, and give an output.” pg. 84 §4; Fig. 4B];
step 4, repeating steps 2 to 3 until a n-th DeepES unit completes its operation [multi-layer Fig. 4B];
step 5, calculating a predicted value Y based on the three factors that are outputted from a final DeepES unit [Output Fig. 4B].
It would have been obvious to one having ordinary skill in the art, having the teachings of Jiang and Han before him before the effective filing date of the claimed invention, to modify the method of Jiang to substitute the fruit fly optimization algorithm of Jiang with the artificial neural network of Han.
Given the advantage of a simple substitution of known algorithms to obtain predictable results, one having ordinary skill in the art would have been motivated to make this obvious modification.
Regarding Claim 2, Jiang and Han disclose the interpretable power load prediction method according to claim 1. Jiang further discloses wherein
steps 1 to 3 comprise: constructing a network framework;
setting an activation function within the network framework and utilizing the network framework to calculate the states of the three factors for the time t+1 [“trend, stationarity, and seasonal components of time series” §2.1 ¶2; “α, β, and γ are smoothing parameters of the HW model” §2.1 ¶2; “t is the period of training data” §2.1 ¶2; Equations 2-4 §2.1 ¶2] in the current DeepES unit;
outputting, by the current DeepES unit, the St+1, Tt+1, and It+1 [“trend, stationarity, and seasonal components of time series” §2.1 ¶2; “α, β, and γ are smoothing parameters of the HW model” §2.1 ¶2; “t is the period of training data” §2.1 ¶2; Equations 2-4 §2.1 ¶2] calculated by the network framework to the next DeepES unit.
However, Jiang fails to explicitly disclose wherein
steps 1 to 3 comprise: constructing a network framework;
setting an activation function within the network framework and utilizing the network framework to calculate the states of the three factors for the time t+1 in the current DeepES unit;
outputting, by the current DeepES unit, the St+1, Tt+1, and It+1 calculated by the network framework to the next DeepES unit.
Han discloses wherein
steps 1 to 3 comprise: constructing a network framework [“multi-layer perception in an artificial neural network” Fig. 4B];
setting an activation function within the network framework and utilizing the network framework to calculate the states of the three factors for the time t+1 in the current DeepES unit [“The function that receives an input signal and produces an output signal after a certain threshold value is called an activation function.” pg. 85, ¶1; “artificial neural networks predominantly use a weight modification method in the learning process” pg. 85 ¶1];
outputting, by the current DeepES unit, the St+1, Tt+1, and It+1 calculated by the network framework to the next DeepES unit [“In an artificial neural network, the first layer (input layer) has input neurons that transfer data via synapses to the second layer (hidden layer), and similarly, the hidden layer transfers this data to the third layer (output layer) via more synapses.” pg. 86 ¶1].
It would have been obvious to one having ordinary skill in the art, having the teachings of Jiang and Han before him before the effective filing date of the claimed invention, to modify the method of Jiang to substitute the fruit fly optimization algorithm of Jiang with the artificial neural network of Han.
Given the advantage of a simple substitution of known algorithms to obtain predictable results, one having ordinary skill in the art would have been motivated to make this obvious modification.
Claim 13 is rejected on the same grounds as claim 1. Jiang further discloses an initialization module, a first state calculation module, an iterative calculation module, and a prediction module [“implemented on MATLAB R2016b using an in-house software executed on a computer with Intel Core i5-6500 3.2 GHz CPU,16 GB RAM, and running the Microsoft Windows 7 Pro operating system.” §3 ¶2].
Claim 14 is rejected on the same grounds as claim 1. Jiang further discloses a memory, used for storing a computer program that is executable on a processor; a processor, used for executing the computer program [“implemented on MATLAB R2016b using an in-house software executed on a computer with Intel Core i5-6500 3.2 GHz CPU,16 GB RAM, and running the Microsoft Windows 7 Pro operating system.” §3 ¶2].
No Prior Art Rejections
As best as the claims are understood, claims 3-12 do not have prior art rejections. Specifically, claim 3 equations and initialization approach in light of the claim as a whole were not found in the prior art. Claims 5 and 8’s calculation formulas of the smoothing factor approach in light of the claim as a whole were not found in the prior art. Claims 11 and 12’s calculation formula and network parameters in light of the claim as a whole were not found in the prior art.
Examiner’s Note
The Examiner respectfully requests of the Applicant in preparing responses, to fully consider the entirety of the reference(s) as potentially teaching all or part of the claimed invention. It is noted, REFERENCES ARE RELEVANT AS PRIOR ART FOR ALL THEY CONTAIN. “The use of patents as references is not limited to what the patentees describe as their own inventions or to the problems with which they are concerned. They are part of the literature of the art, relevant for all they contain.” In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). A reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art, including non-preferred embodiments (see MPEP 2123). The Examiner has cited particular locations in the reference(s) as applied to the claim(s) above for the convenience of the Applicant. Although the specified citations are representative of the teachings of the art and are applied to the specific limitations within the individual claim(s), typically other passages and figures will apply as well.
Additionally, any claim amendments for any reason should include remarks indicating clear support in the originally filed specification.
Conclusion
Any prior art made of record and not relied upon is considered pertinent to Applicant's disclosure. Applicant is reminded that in amending in response to a rejection of claims, the patentable novelty must be clearly shown in view of the state of the art disclosed by the references cited and the objections made. Applicant must also show how the amendments avoid such references and objections. See 37 CFR §1.111(c). Additionally when amending, in their remarks Applicant should particularly cite to the supporting paragraphs in the original disclosure for the amendments.
The following references were found during the examination of this patent application and were found to be relevant to patentability. Applicant is advised to review these references prior to responding to this Office action.
Katsialos et al. (HOLT-WINTERS AND NEURAL-NETWORK METHODS FOR MEDIUM-TERM SALES FORECASTING) discloses a hybrid FMNN-based approach, whereby we keep the smoothing equations (3)-(5) of the Holt-Winters method (with ad-hoc parameters α=β=0.1 ) to produce the current level Lt, trend bt, and seasonality St, and apply subsequently a FMNN, instead of the extrapolation equation (6) to produce the forecasts Ft+m (m = 1,4,18,22 for data groups D5-D8).
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/R.B./ Examiner, Art Unit 2148
/MICHELLE T BECHTOLD/ Supervisory Patent Examiner, Art Unit 2148
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